Supporting exploratory text analysis in literature study.
We present WordSeer, an exploratory analysis environment for literary text. Literature study is a cycle of reading, interpretation, exploration, and understanding. While there is now abundant technological support for reading and interpreting literary text in new ways through text-processing algorit...
| Publicado en: | Literary & Linguistic Computing Vol. 28; no. 2; pp. 283 - 296 |
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| Autores principales: | , |
| Formato: | Artículo |
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Oxford University Press / USA
Jun2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=87826450&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 87826450 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 02681145 BJ1 jtl: Literary & Linguistic Computing issn: 02681145 maglogo: N pubinfo: dt: Jun2013 vid: 28 iid: 2 pid: 622 pub: Oxford University Press / USA artinfo: ui: 87826450 10.1093/llc/fqs044 ppf: 283 ppct: 13 formats: fmt: @attributes: type: P size: 1.2MB tig: atl: Supporting exploratory text analysis in literature study. aug: au: Muralidharan, Aditi Hearst, Marti A. affil: University of California at Berkeley, USA su: Literature Text processing (Computer science) Algorithms Sensemaking theory (Communication) Grammaticalization Language & languages sug: subj: Literature Text processing (Computer science) Algorithms Sensemaking theory (Communication) Grammaticalization Language & languages ab: We present WordSeer, an exploratory analysis environment for literary text. Literature study is a cycle of reading, interpretation, exploration, and understanding. While there is now abundant technological support for reading and interpreting literary text in new ways through text-processing algorithms, the other parts of the cycle—exploration and understanding—have been relatively neglected. We are motivated by the literature on sensemaking, an area of computer science devoted to supporting open-ended analysis on large collections of data. Our software system integrates tools for algorithmic processing of text with interaction techniques that support the interpretive, exploratory, and note-taking aspects of scholarship. At present, the system supports grammatical search and contextual similarity determination, visualization of patterns of word context, and examination and organization of the source material for comparison and hypothesis building. This article illustrates its capabilities by analyzing language-use differences between male and female characters in Shakespeare’s plays. We find that when love is a major plot point, the language Shakespeare uses to refer to women becomes more physical, and the language referring to men becomes more sentimental. Future work will incorporate additional sensemaking tools to aid comparison, exploration, grouping, and pattern recognition. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Literary & Linguistic Computing holder: Oxford University Press / USA dt: @attributes: year: 2013 holdings: @attributes: islocal: N |
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